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Main Authors: Blum, Avrim, Diana, Emily, Ravichandran, Kavya, Tolbert, Alexander Williams
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.04462
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author Blum, Avrim
Diana, Emily
Ravichandran, Kavya
Tolbert, Alexander Williams
author_facet Blum, Avrim
Diana, Emily
Ravichandran, Kavya
Tolbert, Alexander Williams
contents In this paper, we relate the philosophical literature on pessimism traps to information cascades, a formal model derived from the economics and mathematics literature. A pessimism trap is a social pattern in which individuals in a community, in situations of uncertainty, begin to copy the sub-optimal actions of others, despite their individual beliefs. This maps nicely onto the concept of an information cascade, which involves a sequence of agents making a decision between two alternatives, with a private signal of the superior alternative and a public history of others' actions. Key results from the economics literature show that information cascades occur with probability one in many contexts, and depending on the strength of the signal, populations can fall into the incorrect cascade very easily and quickly. Once formed, in the absence of external perturbation, a cascade cannot be broken -- therefore, we derive an intervention that can be used to nudge a population from an incorrect to a correct cascade and, importantly, maintain the cascade once the subsidy is discontinued. We study this both theoretically and empirically.
format Preprint
id arxiv_https___arxiv_org_abs_2406_04462
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Pessimism Traps and Algorithmic Interventions
Blum, Avrim
Diana, Emily
Ravichandran, Kavya
Tolbert, Alexander Williams
Social and Information Networks
In this paper, we relate the philosophical literature on pessimism traps to information cascades, a formal model derived from the economics and mathematics literature. A pessimism trap is a social pattern in which individuals in a community, in situations of uncertainty, begin to copy the sub-optimal actions of others, despite their individual beliefs. This maps nicely onto the concept of an information cascade, which involves a sequence of agents making a decision between two alternatives, with a private signal of the superior alternative and a public history of others' actions. Key results from the economics literature show that information cascades occur with probability one in many contexts, and depending on the strength of the signal, populations can fall into the incorrect cascade very easily and quickly. Once formed, in the absence of external perturbation, a cascade cannot be broken -- therefore, we derive an intervention that can be used to nudge a population from an incorrect to a correct cascade and, importantly, maintain the cascade once the subsidy is discontinued. We study this both theoretically and empirically.
title Pessimism Traps and Algorithmic Interventions
topic Social and Information Networks
url https://arxiv.org/abs/2406.04462